From: François Fleuret Date: Sun, 12 Mar 2023 07:19:36 +0000 (+0100) Subject: Update X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=c4eb660976808b873f32fe873819c4988aaf2ea5;p=beaver.git Update --- diff --git a/beaver.py b/beaver.py index b0e8a78..7adb804 100755 --- a/beaver.py +++ b/beaver.py @@ -26,9 +26,7 @@ else: ###################################################################### -parser = argparse.ArgumentParser( - description="An implementation of GPT with cache to solve a toy geometric reasoning task." -) +parser = argparse.ArgumentParser(description="A maze shortest path solving with a GPT.") parser.add_argument("--log_filename", type=str, default="train.log") @@ -196,7 +194,6 @@ class TaskMaze(Task): ) mazes_train, paths_train = mazes_train.to(device), paths_train.to(device) self.train_input = self.map2seq(mazes_train, paths_train) - self.nb_codes = self.train_input.max() + 1 mazes_test, paths_test = maze.create_maze_data( nb_test_samples, @@ -208,6 +205,8 @@ class TaskMaze(Task): mazes_test, paths_test = mazes_test.to(device), paths_test.to(device) self.test_input = self.map2seq(mazes_test, paths_test) + self.nb_codes = self.train_input.max() + 1 + def batches(self, split="train", nb_to_use=-1): assert split in {"train", "test"} input = self.train_input if split == "train" else self.test_input diff --git a/mygpt.py b/mygpt.py index 5ea4668..df6eab6 100755 --- a/mygpt.py +++ b/mygpt.py @@ -14,19 +14,6 @@ from torch.nn import functional as F ###################################################################### - -class WithResidual(nn.Module): - def __init__(self, *f): - super().__init__() - self.f = f[0] if len(f) == 1 else nn.Sequential(*f) - - def forward(self, bs): - bs.x = bs.x + self.f(bs).x - return bs - - -###################################################################### - # A BracketedSequence is a BxTx... tensor with a first and a nb time # steps to compute. @@ -57,6 +44,19 @@ class BracketedSequence: ###################################################################### +class WithResidual(nn.Module): + def __init__(self, *f): + super().__init__() + self.f = f[0] if len(f) == 1 else nn.Sequential(*f) + + def forward(self, bs): + bs.x = bs.x + self.f(bs).x + return bs + + +###################################################################### + + class CacheWrapper(nn.Module): def __init__(self, *f): super().__init__()